--- license: apache-2.0 tags: - generated_from_trainer datasets: - financial_phrasebank metrics: - recall - accuracy - precision model-index: - name: TOMFINSEN results: - task: name: Text Classification type: text-classification dataset: name: financial_phrasebank type: financial_phrasebank args: sentences_50agree metrics: - name: Recall type: recall value: 0.8985861629736692 - name: Accuracy type: accuracy value: 0.8742268041237113 - name: Precision type: precision value: 0.8509995913451198 --- # TOMFINSEN This model is a fine-tuned version of [deepmind/language-perceiver](https://huggingface.co/deepmind/language-perceiver) on the financial_phrasebank dataset. It achieves the following results on the evaluation set: - Loss: 0.3642 - Recall: 0.8986 - Accuracy: 0.8742 - Precision: 0.8510 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 16 - eval_batch_size: 16 - seed: 42 - distributed_type: tpu - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 4 ### Training results | Training Loss | Epoch | Step | Validation Loss | Recall | Accuracy | Precision | |:-------------:|:-----:|:----:|:---------------:|:------:|:--------:|:---------:| | 0.5403 | 1.0 | 273 | 0.4207 | 0.8358 | 0.8619 | 0.8534 | | 0.3939 | 2.0 | 546 | 0.3750 | 0.8943 | 0.8577 | 0.8225 | | 0.1993 | 3.0 | 819 | 0.3113 | 0.8882 | 0.8660 | 0.8367 | | 0.301 | 4.0 | 1092 | 0.3642 | 0.8986 | 0.8742 | 0.8510 | ### Framework versions - Transformers 4.15.0 - Pytorch 1.9.0+cu102 - Datasets 1.17.0 - Tokenizers 0.10.3